class_docstr: TensorboardManager stores tensorboard logs (tfevent files, .gz zipped archives,
  and .pb protobuf graph and model definition files) to a supported storage backend. The
  trial will generate tfevent files during training. If a profiling callback is used,
  .pb and .gz files will also be generated. These files must be written to the same
  base_path as the base_path used in the constructor of this class.
  
  Each supported persistent storage backend must define a subclass which
  implements the sync method.
docstr: Save the object to the backing persistent storage.
docstr_tok: ["Save","the","object","to","the","backing","persistent","storage","."]
code: def _sync_impl(self, path_info_list: List[PathUploadInfo]) -> None:
      """
      Save the object to the backing persistent storage.
      """
      pass
  
imports: import abc
  import logging
  import pathlib
  import queue
  import threading
  import time
  from dataclasses import dataclass
  from typing import Any, Callable, List
  from determined import tensorboard
  from determined.common import util
label_desc: Use image node_id 4 for calling the TensorboardManager obj's underlying member method code with example usage: obj._sync_impl(path_info_list) without return types